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» Evaluating algorithms that learn from data streams
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99
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SIGMOD
2004
ACM
188views Database» more  SIGMOD 2004»
16 years 23 days ago
Online Event-driven Subsequence Matching over Financial Data Streams
Subsequence similarity matching in time series databases is an important research area for many applications. This paper presents a new approximate approach for automatic online s...
Huanmei Wu, Betty Salzberg, Donghui Zhang
125
Voted
CGI
2009
IEEE
15 years 4 months ago
Easy integral surfaces: a fast, quad-based stream and path surface algorithm
Despite the clear benefits that stream and path surfaces bring when visualizing 3D vector fields, their use in both industry and for research has not proliferated. This is due, in...
Tony McLoughlin, Robert S. Laramee, Eugene Zhang
JAIR
2010
111views more  JAIR 2010»
14 years 11 months ago
Training a Multilingual Sportscaster: Using Perceptual Context to Learn Language
We present a novel framework for learning to interpret and generate language using only perceptual context as supervision. We demonstrate its capabilities by developing a system t...
David L. Chen, Joohyun Kim, Raymond J. Mooney
168
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VLDB
2007
ACM
295views Database» more  VLDB 2007»
15 years 6 months ago
From Data Privacy to Location Privacy: Models and Algorithms
This tutorial presents the definition, the models and the techniques of location privacy from the data privacy perspective. By reviewing and revising the state of art research in ...
Ling Liu
ICASSP
2010
IEEE
15 years 25 days ago
Learning from high-dimensional noisy data via projections onto multi-dimensional ellipsoids
In this paper, we examine the problem of learning from noisecontaminated data in high-dimensional space. A new learning approach based on projections onto multi-dimensional ellips...
Liuling Gong, Dan Schonfeld